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Other topics include chaos in optical communications, channel equalization for chaotic communications systems, using coupled maps to improve synchronization performance, blind source separation in the context of deterministic signals, isochronal synchronization and digital chaos-based communication, and the robustness of chaos to multipath propagation media.
Independent Component Analysis (ICA), a computationally efficient blind source separation technique, has been an area of interest for researchers for many practical applications in various fields of science and engineering.
First, the basic approach to time-frequency masking in blind source separation is introduced.
Blind Source Separation (BSS) has received considerable attention in the latest decade in many research fields, such as communications, speech separation and signal processing and control , .
SCR researchers have come up with a way of singling out meaningful signals from a cacophony of signals mixed together in an electronic "Tower of Babel" or babble, using Blind Source Separation (BSS) techniques.
Mixing Matrix Estimation in Blind Source Separation Based on Generalized Gaussian Mixture Modal
Among specific topics are an efficient content delivery algorithm for intermittently connected mobile ad hoc networks, a niche genetic algorithm with permutation distance in laser anti-missile problems, matching a set of patterns with wildcards, an improved web page ranking algorithm based on temporal information, tracking control and synchronization design for chaotic systems, and tow-ship interference suppression based on blind source separation for passive sonar.
This method regards the problem of watermark detection as a blind source separation problem, and thus uses independent component analysis to estimate the embedded watermark.